Effect of Speed Limit Increase on Crash Rate on Rural Two-lane Highways in Louisiana

Effect of Speed Limit Increase on Crash Rate on Rural Two-lane Highways in Louisiana
Author: Chester G. Wilmot
Publisher:
Total Pages: 102
Release: 2006
Genre: Rural roads
ISBN:

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This study investigated the impact of a speed limit increase on the crash rate on rural twolane roads in Louisiana. The Louisiana crash database for 1999-2004 was used to compare rates of different crash severities and types before and after a speed limit change on rural roads during the observation period.

Investigation of Traffic Crashes in Two-lane Rural Highways in Ohio

Investigation of Traffic Crashes in Two-lane Rural Highways in Ohio
Author: Abdullah Alhomidan
Publisher:
Total Pages: 133
Release: 2006
Genre: Highway engineering
ISBN:

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Traffic crashes continue to be a major concern on the U.S roads. Rural highways represent the largest single class of highways in the United States, and account for approximately 80 percent of all paved highways. Two-lane highways compose of more than 85 per cent of all rural highways. Most of the existing studies on the deer-vehicle-crash (DVC) and run-off-road (ROR) crashes are based on crash reports only, and there are some conflicting findings on the major contributing factors to the crashes. In this study we investigate the most common types of crashes on two-lane rural highways. We find that the deer-vehicle-crashes and the run-off-road crashes represent the majority of the crashes in a sample of 1208 non-intersections crashes that occurred in 173.5 miles of roadways in the Ashtabula County, Ohio. The investigation procedure begins with identifying the high crashes sections, followed by field surveys, and statistical analysis. The statistical analysis showed that the percentage of the wooded area located less than 30 ft from the highway edge is the most important factor that can be used to distinguish the high DVC sections from the other sections. Similarly, the percentage of the non-forgiving shoulders is the most important factor to distinguish between the high ROR sections from the other sections. In addition, the correlation analysis showed weak connection between the high DVC sections and the high ROR sections. Field experiments have been conducted to collect additional data unavailable in the crash reports. The experimental results suggest that the depth of clear zone (by removing trees and bushes) in the wooded area should be no more than 40 ft on each side of the highway. To increase highway lights, the areas that need to be lit are between 27 to 38 feet from the side of the highway. The results also suggest that deer warning signs have little influence on the drivers to reduce speeds or switch from low to high beams. Future studies may include investigation of the effectiveness of the countermeasures for DVC. Additional work is also needed to study the behavioral factors of drivers in the ROR crashes once data are available.

Characteristics of Drivers who Cause Run-off-road-crashes on Ohio Roadways

Characteristics of Drivers who Cause Run-off-road-crashes on Ohio Roadways
Author: Abdullah Faleh Alruwaished
Publisher:
Total Pages: 70
Release: 2014
Genre: Automobile drivers
ISBN:

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A vehicle that leaves its travel lane at a non-intersection location and collides with another vehicle or with a fixed object or overturns is considered to be involved in a run-off-road (ROR) crash. ROR crashes also known as roadway departure crashes, and these include head-on crashes, crashes that occur due to lane shifts, and crashes where the vehicle leaves its designated travel lane. The main objective of this study was to identify the significant factors that lead to these types of crashes. Crash data used in this study were obtained from the Ohio Department of Public Safety for a five-year period from 2008 to 2012. The classification tree modeling was used in this study to investigate the significant predictor variables of crash severity of ROR crashes. In addition, this thesis study developed two models, the ROR crashes model and the non-run-off-road (NROR) crashes model. The NROR crashes model used crash data for drivers who were at fault when their crash incidents occurred and for ROR crashes; it was assumed that all drivers in this category were at fault of causing the crashes. The ROR model identified nine variables, which include road condition, collision type, alcohol related, posted speed limit, speed related, crash type, vehicle type, gender, and age. The NROR crashes model has six significant predictor variables including collision type, posted speed limit, speed related, road condition, alcohol related, and vehicle type.

Characteristics of Injury and Fatality of Run-off-road Crashes on Ohio Roadways

Characteristics of Injury and Fatality of Run-off-road Crashes on Ohio Roadways
Author: Omar Eid Almutairi
Publisher:
Total Pages: 77
Release: 2013
Genre: Accident victims
ISBN:

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A run-off-road (ROR) crash or a roadway departure crash is a non-intersection crash which occurs after a vehicle crosses an edge line or a center line (i.e., leaves its designated traveled way and in the process the vehicle collides with a non-traversable obstacle or another vehicle travelling in the opposite direction or hits a pedestrian, or the vehicle overturns. The main objective of this thesis study was to determine the factors that contribute significantly to the levels of injury severity when ROR crashes occur. This study used a 5-year crash data for years 2008 - 2012 obtained from the Ohio Department of Public Safety. The decision tree model in conjunction with generalized ordered logit model was used to investigate characteristics of injury and fatality of run-off-road crashes in Ohio. The decision tree modeling was used for exploratory data analysis identified eight factors that explain a large amount of the variation in the response variable, injury severity. These important predictors for injury severity include road condition, run-off-road (ROR) crash types, posted speed limit, vehicle type, gender, alcohol-related, road contour, and drug-related. Also, complex interactions between parameters were identified. The results from the generalized ordered logit regression show that the following are significant factors in increasing the likelihood of ROR injury severity levels: alcohol and drugs use, curves and grades, female victims, overturn/rollover crashes, ROR crashes on dry roadway surfaces. Additionally, buses, truck, and emergency vehicles, and ROR crashes on roadways with posted speed limits of 40 mph or higher increase the probability of injury severity.

Data Analytics for Smart Cities

Data Analytics for Smart Cities
Author: Amir Alavi
Publisher: CRC Press
Total Pages: 240
Release: 2018-10-26
Genre: Computers
ISBN: 0429786638

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The development of smart cities is one of the most important challenges over the next few decades. Governments and companies are leveraging billions of dollars in public and private funds for smart cities. Next generation smart cities are heavily dependent on distributed smart sensing systems and devices to monitor the urban infrastructure. The smart sensor networks serve as autonomous intelligent nodes to measure a variety of physical or environmental parameters. They should react in time, establish automated control, and collect information for intelligent decision-making. In this context, one of the major tasks is to develop advanced frameworks for the interpretation of the huge amount of information provided by the emerging testing and monitoring systems. Data Analytics for Smart Cities brings together some of the most exciting new developments in the area of integrating advanced data analytics systems into smart cities along with complementary technological paradigms such as cloud computing and Internet of Things (IoT). The book serves as a reference for researchers and engineers in domains of advanced computation, optimization, and data mining for smart civil infrastructure condition assessment, dynamic visualization, intelligent transportation systems (ITS), cyber-physical systems, and smart construction technologies. The chapters are presented in a hands-on manner to facilitate researchers in tackling applications. Arguably, data analytics technologies play a key role in tackling the challenge of creating smart cities. Data analytics applications involve collecting, integrating, and preparing time- and space-dependent data produced by sensors, complex engineered systems, and physical assets, followed by developing and testing analytical models to verify the accuracy of results. This book covers this multidisciplinary field and examines multiple paradigms such as machine learning, pattern recognition, statistics, intelligent databases, knowledge acquisition, data visualization, high performance computing, and expert systems. The book explores new territory by discussing the cutting-edge concept of Big Data analytics for interpreting massive amounts of data in smart city applications.

Public Roads

Public Roads
Author:
Publisher:
Total Pages: 44
Release: 1983
Genre: Highway research
ISBN:

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